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INNOVATIVE METHODOLOGY
1Imaging Research Laboratories, Robarts Research Institute, London, Ontario; 2Lawson Health Research Institute, London, Ontario; and Departments of 3Physiology and Pharmacology, 4Medical Biophysics, and 5Diagnostic Radiology and Nuclear Medicine, University of Western Ontario, London, Ontario, Canada
Submitted 3 June 2006 ; accepted in final form 19 January 2007
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ABSTRACT |
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lung volume; airway diameter; tidal volume; functional residual capacity
Specialized micro-computed tomography (micro-CT) scanners that provide high-resolution, low-noise CT images of rodents have been developed (24, 49). These scanners are commercially available and are routinely used to noninvasively image rodent models of human disease. Ex vivo micro-CT studies have been used to assess acute lung injury in fixed rat lungs (35) and in fresh excised rat lungs (55). For quantitative measurements of lung microstructures and airways, segmentation algorithms have been implemented for ex vivo micro-CT scans of human lung specimens (59) and Siliastic lung casts obtained from mice and dogs (9). Micro-CT studies have also been performed in vivo to detect lung tumors (12) and to monitor tumor growth and treatment (29) in mice. In vivo imaging of rodent lung morphology has additional challenges because of the high respiration rates in mice and rats; therefore, multiple breathing cycles will occur during a micro-CT scan, which could last up to 30 min per scan.
Throughout the respiratory cycle, the thorax and upper abdomen experience motion, which causes artifacts in the CT image, including blurring of the lungs (39). Clinically, these artifacts can be avoided by acquiring the CT projections during a breath hold; however, this breath-hold technique is not feasible for imaging rodents because the acquisition time for the majority of commercially available micro-CT equipment ranges from 10 to 30 min per scan. To eliminate artifacts caused by respiratory motion in rodents, or to capture an image of a selected phase of the respiratory cycle, the micro-CT image acquisition can be synchronized to the respiratory cycle. Other researchers have implemented prospective respiratory-gating protocols with commercial micro-CT equipment (8, 57) or with custom-made micro-CT equipment (1). This strategy requires that the animal be intubated and that an output signal from the ventilator be used to initiate the acquisition of the projection image. Hu et al. (25) opted for a retrospective approach, where images are acquired throughout the respiratory cycle, but only the projections that are in the same respiratory phase are reconstructed. However, the process of intubation, used in all the studies mentioned, requires specialized animal handling skills, and it may introduce damage to the upper airways if performed incorrectly (6). Intubation also requires the animals to be anesthetized and paralyzed, which changes the respiratory mechanics and lung function of the animal (23). In addition, the pressure and volume settings used to ventilate the animal can affect the morphology and mechanics (20, 43–45).
To provide a noninvasive imaging tool, the micro-CT imaging must be done while the animals are free breathing. An approach for respiratory-gated micro-CT of free-breathing rodents has been described previously (17), and it was utilized for the present work. In our method, the respiratory waveform of an anesthetized, free-breathing mouse or rat is determined by the external motion of the diaphragm. The measured waveform is used to trigger the acquisition of projection images during the desired respiratory phase. Once reconstructed, the resulting three-dimensional volumetric image depicts the thorax over a specific, preselected, portion of the respiratory cycle, and it minimizes the artifacts caused by respiratory motion.
In this paper, we present a quantitative technique for noninvasively investigating lung morphology in rodents. Using respiratory-gated micro-CT, we imaged healthy, anesthetized free-breathing mice during inspiration and end expiration. Measurements of airway diameter, lung volume, and mean lung density were obtained, and tidal volume (VT) and functional residual capacity (FRC) were derived from the three-dimensional micro-CT images.
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METHODS |
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4 h between scans. All animal studies complied with the regulations set out by the Animal Use Subcommittee of the Council on Animal Care at the University of Western Ontario. Micro-CT scanning. Prospective respiratory-gated micro-CT scans of the free-breathing mice were based on a respiratory-gating technique described previously (17). Briefly, the animal was positioned in the scanner lying prone on a custom-made polycarbonate bed, with its abdomen over an air-filled chamber that was covered with a thin polyvinyl chloride film. Diaphragm motion induced a pressure change in the chamber, which was detected by a pressure transducer. The trigger signal from the transducer, which originated at the beginning of inspiration, could be delayed to coincide with any portion of the respiratory cycle and was used to trigger the X-ray acquisition. The mice were lightly restrained to ensure a reliable respiratory signal from the external monitoring device, as shown in Fig. 1. The respiratory waveform was monitored before imaging to set the trigger timing. For images acquired at end expiration, the trigger was positioned at the beginning of the plateau between breaths, and for the images acquired at inspiration, the trigger was positioned at the beginning of the breath, as shown in Fig. 2. Images were acquired during a nominal frame exposure of 100 ms, chosen because the rapid respiratory rates of mice require short acquisition times and because 100 ms represents the shortest acquisition time for this scanner. The effective frame exposure for this protocol was measured to be 170 ms of X-ray exposure, because of the time interval required for the shutter to open and close. The externally measured respiration waveform and trigger signal were recorded throughout the scans.
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4 h before a second scan, acquired during inspiration, was taken in the afternoon. Images were reconstructed using a modified Feldkamp algorithm (15) with a nominal isotropic voxel spacing of 90 µm, and they were scaled into Hounsfield units (HU). In CT, images are normalized relative to water to allow accurate comparisons of images from different scanners or studies, such that image values are the following: 0 HU for water, –1,000 HU for air, typically ranging from –150 to 100 HU for soft tissue, and typically greater than 1,000 HU for cortical bone. A calibration scan of a plastic tube filled with water positioned on the gating bed was performed using the same scanning protocol. In this scan, the water in the tube was set to 0 HU, and the surrounding air was set to –1,000 HU. The respiratory-gating bed was found to have a CT number of –60 HU. To scale the mouse image into HUs, the air in the trachea was set to –1,000 HU (38), and the respiratory-gating bed was set to –60 HU for each three-dimensional volumetric image.
Respiratory waveform analysis.
To ensure that the respiratory waveform recorded during each scan was consistent between the inspiration and end-expiration imaging sessions for each mouse, and that the respiratory patterns were similar for the entire population of mice, the respiratory waveforms were analyzed. The analysis was performed using Chart 5 software (v5.0.1, ADInstruments, Colorado Springs, CO), which was also used to record the respiratory waveforms during the micro-CT scan. The respiratory curves were baseline corrected so that the plateau between breaths was taken as zero. Measured values included the global maximum value, global minimum value, the average maximum, average breath, the number of breaths per minute, and the number of gasps during the scan. The maximum value was taken as the highest value, excluding sighs or gasps. The percent difference compared the maximum value to the average maximum value, using the relationship given in Eq. 1.
 | (1) |
Because the mice were restrained for each scan, we wanted to ensure that the amount of tension applied to the abdomen was not excessive, such that the respiratory motion and function were not altered due to the restraint. Using the first five mice that were imaged in this study, the analysis of the respiratory waveform and the image analysis were performed. From these data, inconsistent results in the measured lung morphology (airway diameters and lung volumes) were observed, indicating that the amount of tension applied to the animal was changing between the scans acquired at the different phases of the respiratory cycle. An exclusion criterion, based on the respiratory waveform alone, was determined to remove animals from the image analysis that were restrained too tightly during their micro-CT scan. Two criteria were considered, gasps and uneven breathing patterns, as defined below:
When a respiratory waveform was deemed unsuitable, using the criteria above, the animal was removed from further analysis, even if some of the data from that animal was usable. Using these two criteria, we hoped to remove any animals from further analysis that were experiencing uneven breathing patterns (criterion 1) or were restrained too tightly (criterion 2) during the scan. For the remainder of the imaging sessions (9 mice at both respiratory phases), the tension applied to the abdomen using the restraining strap was adjusted to ensure that the mice were not restrained too tightly during the scan.
Image analysis. Image analysis was performed using MicroView (2.1.1, General Electric Healthcare, London, Canada). For each mouse, the corresponding inspiration and end-expiration images were registered and reoriented so that the major airways (trachea and bronchi) were aligned with one of the axes of the image. Registration was performed by manually selecting corresponding bony landmarks in both images (along the spine, sternum, and ribs) and applying a rigid-body three-dimensional transformation to register the volumes. A cubic interpolation was used during the reorientation of the three-dimensional volumes to minimize artifacts to the point where we have not found that it degrades measurements of dimension. A region of interest (ROI) was drawn, beginning 2 mm superior to the carina and extending to include the full extent of the lungs. Minimum-intensity projections were obtained through the ROI. In a minimum-intensity projection image, the minimum value in each column through the three-dimensional volume is recorded in a two-dimensional projection image. For the mouse images, the minimum-intensity projection image was generated through the coronal plane. Using the minimum-intensity projection image, the diameter of the trachea was measured 2 mm superior to the carina. The diameter of the left bronchus was measured 2 mm inferior to the carina, and the right bronchus at 1.5 mm inferior the carina, which roughly corresponds to the widest part of the airway before the next generation branches off. The lengths of the left and right lungs, from the apex to the lower tip, were also measured for each minimum-intensity projection image. For each of the diameter measurements, the full-width at half-maximum was used to eliminate errors due to partial volume effects or any difficulties in locating the boundary of the airway or the lung. To measure the diameter of the airway, a line was drawn across the minimum projection image at the designated location that extended beyond the edges of the airway. The gray-scale values along the line were plotted, with the values ranging from a value of up to 100 HU in tissue to a value of approximately –1,000 HU in the airway. The value halfway between the air and the tissue was calculated (half-maximum), and the width of the airway was measured on the histogram graph (distance between the 2 edges of the airway) at the half-maximum value.
Using an automatic threshold selection method similar to Otsu (46), based on the histogram of the gray-scale values within the lungs, two threshold values were obtained: one to separate the lungs from the rest of the soft tissue in the thorax and the other to separate the major airways from the rest of the lungs. Thresholds were obtained by drawing a ROI in the thorax, encompassing lung and surrounding soft tissue in approximately equal amounts, and excluding the major airways. A histogram of the gray-scale values within the ROI has a bimodal distribution, and the gray-scale value corresponding to the minimum number of pixels, which occurs between the two peaks, will separate the CT numbers into the two tissue types. The automatically selected gray-scale value that separates the pixels in the image into lung tissue and the surrounding soft tissue is the threshold value, which will be used for the remaining analysis. The automatic threshold function provided within the analysis tool (MicroView, 2.1.1, General Electric Healthcare) uses an unsupervised, nonparametric model to maximize the separability of the classes that are defined by gray-scale level. The algorithm returned the value to be used as the threshold (–195 HU) to extract the lungs from the surrounding tissue. This threshold value was used for all of the images at inspiration and at expiration for all mice. To extract the lungs from the surrounding tissue, a seeded region growing algorithm was used to select the contiguous voxels below the threshold value, –195 HU. The volume of the lungs including the airways was determined, which we will refer to as the organ volume, along with the mean lung CT density. Similarly, a ROI was drawn covering the lungs and the large airways, in equal proportions, and the threshold value required to separate the CT numbers corresponding to lung parenchyma and airways was determined (–830 HU). This threshold value was also used for all of the images at inspiration and at expiration for all mice. Using a seeded region growing algorithm, the major airways were extracted, by selecting the voxels with a CT number below the threshold of –830 HU, and the total airway volume and mean airway CT density were determined for the major airways. The lung parenchyma was extracted by selecting the voxels with a gray-scale value between the two thresholds, and the volume and CT density were tabulated for the lung parenchyma, which we have defined as the volume of the lungs excluding the major airways.
The FRC and VT were also calculated for each mouse, based on the measured volumes and mean lung CT densities obtained from the micro-CT images, as described in the equations below:
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 | (3) |
Note that Eqs. 2 and 3 allow for the calculation of VT by considering the fractional air content within the inspiration and expiration volumes of interest, rather than simply subtracting the segmented inspiration and expiration volumes. This density-based approach is required to correct for possible respiratory-induced changes in lung tissue perfusion, as previously described (5, 22, 41).
Statistical analysis. For all measured values, the mean, SD, and SE were calculated for each of the two respiratory phases. Two-tailed paired t-tests (Prism, v4.0a, GraphPad Software, San Diego, CA) were used to compare the values at inspiration and end expiration.
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RESULTS |
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Lung volumes and mean lung densities. Because the images were acquired with isotropic voxels (same spacing in all 3 dimensions), the images can be reformatted to different orientations without introducing interpolation artifacts. Multiplanar reformatted slices in the coronal and the transverse planes are shown in Fig. 4 at inspiration and at end expiration. The window and level of these images were chosen to highlight the differences in CT density between the two respiratory phases. The isotropic voxel spacing for these images was 0.09 mm. The airway diameters and lung lengths are larger in the inspiration images (Fig. 4, B and D), and the airways and air spaces within the lungs are darker than those shown in the expiration images (Fig. 4, A and C). Figure 5 shows surface-rendered images of the entire lungs at inspiration and end expiration. The surface rendering was generated from wire-frame meshes, which were created from the intensity-based region growing algorithm that was used to extract the lungs from the surrounding tissues.
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For free-breathing mice, the FRC was calculated as 0.16 ± 0.03 ml and the VT as 0.09 ± 0.03 ml, and they are reported in Table 3. It is important to note that these functional metrics were measured in anesthetized mice, and the actual FRC and VT will be different from the natural values of mice that are awake. However, obtaining these measurements in free-breathing, nonrestrained, nonanesthetized mice is difficult, but they have been reported using whole body plethysmography (2, 26). In mice suffering from respiratory diseases, lung function will be compromised because of the disease; in addition, the respiratory function of these mice may be further compromised by the anesthesia, which will affect the measured values of VT and FRC in populations of diseased mice.
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DISCUSSION |
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Because the scanning technique employed in this study allows the animals to breathe on their own, functional information can also be gained, namely the FRC, VT, and respiratory rate. To date, there has been very little published in the literature about the natural lung function of mice, because most studies in the literature involve histological examinations of killed animals or involve in vivo experiments with intubated and respirated animals. The technique used in this study is completely noninvasive, aside from the injectable anesthesia, so information about the normal, anesthetized respiration of this group of healthy mice can be determined. To our knowledge, in vivo lung morphology measurements obtained in free-breathing mice, such as airway diameter, airway volume, and lung volume, have not been previously described.
The CT densities reported here (–548 HU at inspiration and –467 HU at expiration) are similar to those reported for 18-wk-old mice (–500 HU) by Lehnert et al. (37), in C57 mice (–561 HU) by Plathow et al. (50), and in C57BL/6 mice using micro-CT (–450 HU) by Zhou et al. (61). In all of these studies, the mice were imaged without respiratory gating, so the measured mean lung density is averaged over the entire respiratory cycle. The mean lung density values reported by Lehnert et al. (37) correspond to a mean lung density value that is halfway between our values measured at inspiration and end expiration. In the study by Plathow et al. (50), the CT densities were measured in 10 representative two-dimensional slices, yielding a range in values of –539 to –590 HU using a clinical CT scanner, with image noise values that are typically less than the noise achieved by micro-CT scanners. Similarly, Zhou et al. (61) measured the CT density in a ROI in the micro-CT images. The observed discrepancy in CT density between the present work, representing measurements encompassing the entire lung, and values reported by Plathow et al. (50) and Zhou et al. (61) may indicate that their density measurements were acquired in different portions of the lung, because of the movement of lung tissues throughout the respiratory cycle. These discrepancies may also be due to differences in how the images were scaled into CT numbers (i.e., air in the trachea was set to –1,000 HU in the present work, but others likely used air outside the animals for scaling instead). One confounding factor with regard to quantitative measurements using this micro-CT scanner is the observation that the CT number for air measured in the trachea is higher than air values at the periphery of the image. This same observation has been reported in clinical applications with humans (56). In this study, we have elected to calibrate our lung density measurements using air values obtained in the trachea, rather than the periphery, as described by Lu et al. (38), who used air in the trachea for calibrating into CT numbers, and Kemerink et al. (28), who report that it may be advisable to select a known region of air and tissue to correct the CT calibration for lung densitometry studies. While we believe that this approach will result in air reference values that more closely represent air within the lung, this calibration procedure may differ from that used by other groups. The difference between the interior (–730 ± 80 HU) and the peripheral (–1,000 ± 60 HU) air attenuation is 27% in this study, and this would cause some changes in the measured volumes and CT densities when the images are calibrated using the air in the trachea as opposed to using air in the periphery of the image. Further investigations with phantoms and animals are required to completely understand the mechanisms by which air signal intensity is elevated in the trachea.
The FRC was measured to be 0.16 ± 0.03 ml for male C57BL/6 mice at 13 wk of age. Using a clinical CT scanner, Mitzner et al. (41) measured the FRC in A/J mice to be 0.27 ml and in C3H/HeJ mice to be 0.35 ml. In Mitzner et al.'s study of 4- to 12-wk-old, free-breathing animals, the FRC ranged from 0.17 to 0.30 ml in A/J mice and from 0.28 to 0.4 ml in C3H/HeJ mice, and it increased with animal age until a plateau was reached at 6 wk. Results from the present study are similar to those reported by Mitzner et al., although the mean value is somewhat lower in this population of C57BL/6 mice. The FRC of C57BL/6 mice was determined to be 0.25 ± 0.01 ml using whole body plethysmography by Lai and Chou (34) in 8- to 12-wk-old respirated animals. Because the animals were respirated, the measured FRC would be more consistent across the population, although it may also be affected by the respirator settings.
VT can be calculated in two ways: 1) by subtracting the volume of the lungs at expiration from the volume of the lungs at inspiration; or 2) using Eq. 3, which weights the volume at each phase by the corresponding air fraction. Each of these methods should yield similar results; however, we found a small discrepancy of 0.03 ml (VT = 0.12 ml for method 1, and VT = 0.09 ml using Eq. 3). We believe that this discrepancy is a measure of the changes in lung blood volume that occur during respiration, as described by Brower et al. (5) and Guerrero et al. (22). In the future, this difference in apparent and derived VT could be used to investigate respiratory-induced changes in lung tissue perfusion. The VT in free-breathing mice has not been previously reported, although the conventional ventilation level for mice is 7 ml/kg. The resulting VT should a ventilator be used for the average 26-g mouse in this study would be 0.18 ml, which is higher than the values measured in this study. The ventilated VT is higher, which likely results from including the upper airways in the VT and possibly from overinflating the lungs. In the case of ventilated animals, the respiratory rates are also fixed, generally at a lower rate than what was measured in the free-breathing animals. The measured VT may be lower in the free-breathing case due to their increased respiratory rate (mean rate in the present study is 141 breaths/min), which can be compared with anesthetized, ventilated mice (100 breaths/min) and with nonanesthetized, free-breathing, adult, male mice with a mean rate of 255 breaths/min, measured with plethysmography by Fairchild (13), which may result in a shallower respiratory pattern.
All of the volume measurements reported in this study were obtained using gray-scale, threshold-based algorithms to separately extract the lungs and the airways. Other extraction algorithms have been reported in the literature, including algorithms to extract the airways (9, 47) and vasculature (19, 60), which could be applied to extracting the lungs.
In this study, we discovered that how the animal was positioned, specifically the amount of tension that was applied to the abdomen to ensure good contact with the pressure chamber in the bed, could vary between the two scans. Because the intent of this study was to report quantitative measurements of lung morphology and function in healthy mice, we chose to exclude the mice that were restrained on the respiratory-gating bed using higher than average applied tension to the abdomen. By excluding these animals, we can attribute the variability in the measured values to natural variation in the population, without concerns that the experimental setup compromised the measurements obtained. To ensure that the respiratory mechanics of the animal were not affected by the restraints used during scanning, we devised an exclusion criteria based on the measured respiratory waveform. By monitoring the respiration before scanning, the restraints could be adjusted to ensure that the tension applied to the abdomen would not interfere with normal, anesthetized respiration during the scan. Although the animals were monitored before scanning to ensure good respiratory mechanics, a few animals were excluded from the analysis due to nonuniform breathing patterns, or gasps. Gasps occurring during the scan would cause the lungs to be inflated differently during the projection acquisition compared with the normal breaths; therefore, multiple gasps in a single scan could affect the image quality and the measurements that were made, which resulted in the animal being excluded from further analysis. In general, the number of gasps observed during a scan is small when compared with the total number of projection images acquired, and, therefore, exclusion based on gasps will not be required for most studies. In addition, the tension applied during the scan needs to be consistent between scans from different respiratory phases to ensure accurate functional information is obtained. To reduce the number of animals excluded based on the setup and positioning of the animal, the scans should be done without repositioning the animal. Alternatively, a method to restrain the animal to ensure the same amount of tension is applied to each animal could be devised, such as a strap with markings for different-sized rodents, which would assist the operator during animal setup. In future experiments using this technique, we expect that fewer animals would be excluded, because of the fact that the operator would be able to observe the respiratory waveform before scanning and could reposition the animal by adjusting the strap tension to produce an satisfactory respiratory waveform for the duration of the experiment.
In addition to monitoring the tension applied to the abdomen, we could refine the scanning protocol to allow the acquisition of both inspiration and end-expiration images during a single dose of anesthesia without repositioning the animal. The maximum current of the X-ray tube, and the step-and-shoot mode of image acquisition limit the scan time required for our imaging technique. For this technique, a reduction in the scan time would also imply a decrease in the number of projection images that were acquired, and a corresponding increase in image noise, which may impact the reliability of the measurements if allowed to exceed some threshold amount, and a decrease in radiation exposure for the animal. Using the present protocol, the scan time for each acquisition is 20–25 min, with an X-ray dose of 0.27 Gy. A reduction in scan time by a factor of 2 (10–15 min per scan), and a corresponding reduction in X-ray dose (0.14 Gy per scan), will cause an increase in image noise by a factor of 
2, which follows from previously published work on image quality in micro-CT (18).
The dose received in each scan for the present protocol (0.27 Gy) is reasonable, given that the lung parenchyma is capable of recovery from sublethal doses of radiation (4, 42, 50, 54). In the study performed by Plathow et al. (50), animals received an estimated radiation dose of 0.62 Gy from CT scanning, spread over 13 scans, with no apparent adverse affects. Mole (42) reports that mice can neutralize 0.25–0.5 Gy when exposed daily to whole body irradiation and that the partial body radiation is neutralized more effectively. Adverse effects of irradiating the thorax include lung fibrosis, pneumonitis, and neoplasia, although previous studies have shown that mice are able to survive these complications following up to 20 repeated radiation exposures of a similar X-ray dose to the imaging studies reported here (48). In addition, the lethal dose to 50% of the population for all types of lung damage in mice is reported to be between 9 and 12 Gy, which is much higher than the dose received during the imaging procedure (14, 53). However, some disease models may be affected by the radiation dose received during scanning; further investigation of the effect of the X-ray dose in longitudinal imaging is needed to ensure that the disease progression or treatment is not affected by the imaging techniques used.
Measurements of lung morphology were made using images that were acquired with a prospective respiratory-gating technique on a readily available micro-CT scanner. Projection images were taken in 170-ms imaging windows during inspiration and end expiration. Due to the high respiratory rates of mice, the 170-ms imaging window used in this study encompassed the entire inspiratory phase, causing a small amount of temporal and motion blurring, both of which could result in reduced image quality and affect the measured parameters. Acquisitions with a shorter imaging window would provide images of a more precisely defined portion of the respiratory phase, including images reconstructed during inhalation, during exhalation, and at peak lung inflation, and they may provide more information about the lung morphology, particularly in respiratory disease models. The micro-CT scanner used in this study, along with most of the commercially available scanners of similar design, do not have sufficient temporal resolution to reduce the imaging window to precisely define the peak inspiration phase in a mouse. The 170-ms imaging window used in this study represents the shortest projection acquisition time that this scanner is able to achieve; further optimization of this scan technique will not improve the temporal resolution achieved by this scanner. However, recent advances in X-ray detector technologies have produced a high-speed, flat-panel volume micro-CT scanner that is now commercially available, similar to the one described by Ross et al. (52) and Kiessling et al. (30) and implemented by Guerrero et al. (21) for lung imaging in rodents. This type of high-speed scanner has the temporal resolution required to obtain projection images in tens of milliseconds, which would enable retrospectively gated scans to be performed over very short periods of the respiratory cycle. In addition, retrospective gating results in the acquisition of images at all phases of the respiratory cycle in a single session without moving the animal (16).
Many respiratory diseases are modeled in mice and rats, including asthma (31, 32) and emphysema (36, 40). In addition, rodent models are used to investigate respiratory response to environmental challenges (10), such as pollutants and allergens, and damage from radiation therapy treatments (37, 50). Our noninvasive, respiratory-gated micro-CT imaging technique for use with free-breathing animals is well suited for studying the changes in lung structure and function in populations of animals affected by respiratory diseases, such as those diseases characterized by a change in lung volume, airway volume, airway diameter, or mean lung density. Other respiratory changes that could be monitored involve lung function and include changes in respiratory rate, FRC, or VT.
Micro-CT is a powerful means of monitoring rodent models of respiratory disease because of the quantitative measurements of lung morphology that can be obtained, as demonstrated in this work. Although the spatial resolution of the micro-CT scanner is not sufficient to visualize the smallest airways and alveolar spaces in mice, the air content of the lungs can be monitored in the entire organ or compared between specific regions. The air content is related to the mean lung density, which yields a value between –1,000 and 0 HU (the CT numbers of pure air and water, respectively) for the specified ROI. Regions of the lung with lower mean lung densities contain more air than those with higher mean lung densities, with a linear relationship between the measured values and the total air content. Therefore, the presence of smaller airways and alveolar spaces can be inferred from the mean lung densities, despite being too small to resolve in the images. An additional advantage for using noninvasive, respiratory-gated micro-CT is that the animal models can be investigated longitudinally, using the same imaging modality that would be used for the clinical diagnosis of respiratory disease.
In conclusion, in this work, we have demonstrated a technique to measure lung morphology from micro-CT images of free-breathing mice. Images acquired at end expiration and during inspiration had sufficient image quality and resolution to visualize and to measure the volume and diameter of large airways and the CT density and volume of the entire organ and the parenchyma volume (without the major airways) in mice. Measured values were significantly different in the inspiration images when compared with the end-expiration images (P < 0.05), with the exception of the CT density of the major airways (P = 0.63) and the respiratory rate (P = 0.51). Because imaging was done on free-breathing mice, the VT and FRC could also be derived, and they were calculated to be 0.09 ± 0.03 ml and 0.16 ± 0.03 ml, respectively. These measurements have not previously been reported for free-breathing rodents. From the results of this study on normal, healthy mice, we believe that respiratory-gated micro-CT imaging will be beneficial for future in vivo, noninvasive studies of respiratory diseases in rodent models.
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
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